用数据科学解码消费者行为的挑战

Valentina Chkoniya
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引用次数: 3

摘要

解读不断变化的消费者行为是全球营销人员面临的最大挑战之一。消费者行为研究的未来受到数据科学进步的质疑。今天,当消费者一直在接触新技术时,面部识别、人工智能和语音技术等趋势并没有像预期的那样迅速发展,营销情报获得了很大的关注。本文概述了从稳健数据集和深度人工智能专业知识的角度预测消费者数据智能发展的可能方法,以便更好地理解、建模和预测消费者行为。在数字过度曝光的时代,营销不能孤立地进行,这需要对消费者行为有更深入的了解。世界各地的数据科学家、分析师和营销人员必须共同努力,提高消费者忠诚度,增加收入,提高模型的预测性和营销支出的有效性。有效地将消费者行为数据整合到营销策略中,可以帮助公司改进吸引和赢得多样化和动态的消费者群体并留住他们的方法。这种对当前研究的综合将有助于研究人员和从业人员利用数据科学来理解和预测消费者行为,以及那些制定长期规划营销决策的人。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Challenges in Decoding Consumer Behavior with Data Science
Decoding the ever-evolving consumer behavior is one of the biggest challenges faced by marketers around the world. The future of consumer behavior research is put into question by the advances in data science. Today, when consumers are all the time exposed to new technologies, trends such as facial recognition, artificial intelligence, and voice technology did not advance as rapidly as predicted, marketing intelligence gained a significant share of the spotlight. This paper gives an overview of possible ways to anticipate consumer data intelligence development from the perspectives of a robust data set and deep artificial intelligence expertise for better understanding, modeling, and predicting consumer behavior. Showing that marketing cannot happen in isolation in the era of digital overexposure, it requires a deeper understanding of consumer behavior. Data scientists, analysts, and marketers around the world have to work together to increase consumer loyalty, grow revenue, and improve the predictiveness of their models and effectiveness of their marketing spend. Efficiently integrating consumer behavior data into marketing strategies can help companies improve their approach towards attracting and winning the diverse and dynamic consumer segments and retaining them. This synthesis of current research will be helpful to both researchers and practitioners that work on the use of data science to understand and predict consumer behavior, as well as those making long-range planning marketing decisions.
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